All maintained schools are required to provide 2 possible sessions per day, morning and afternoon, to all pupils.
The length of each session, break and the school day is determined by the school’s governing body.
Schools must meet for at least 380 sessions or 190 days during any school year to educate their pupils.
If a school is prevented from meeting for 1 or more sessions because of an unavoidable event, it should find a practical way of holding extra sessions.
However, if it cannot find a practical way of doing this then it’s not required to make up the lost sessions.
Academy and free school funding agreements state that the duration of the school day and sessions are the responsibility of the academy trust.
Schools are required to take attendance registers twice a day - once at the start of the first morning session and once during the second afternoon session.
In their register, schools are required to record whether pupils are:
Where a pupil of compulsory school age is absent, schools have a responsibility to:
The parent of every child of compulsory school age is required to ensure their child receives a suitable full-time education for their ability, age, aptitude and any special education needs they may have either by regular attendance at school or otherwise.
Failure of a parent to secure regular attendance of their school registered child of compulsory school age can lead to a penalty notice or prosecution.
Local authorities (LAs) and schools have legal responsibilities regarding accurate recording of a pupil’s attendance.
For further information: School attendance: guidance for schools.
The data used to publish absence statistics is collected via the school census which is used by a variety of companies and organisations including:
The published data is also used in answers to parliamentary questions and public enquiries - including those made under the Freedom of Information Act.
DfE publishes termly pupil absence data and statistics via the following 3 National Statistics releases each year:
Only the full year absence release gives a definitive view of pupil absence.
Termly publications can be affected significantly by term length with findings from these releases for indicative purposes only and the results should be treated with caution.
DfE’s annual absence releases have been badged as National Statistics since the 1999/00 academic year publication.
The termly and two-term combined releases were badged as National Statistics slightly later.
The combined autumn and spring term release was badged as national statistics from the autumn 2006 and spring 2007 publication and the single term releases were badged as National Statistics as of the autumn term 2009 publication.
Prior to the 2012/13 academic year DfE also published spring term only absence data. However, this was discontinued as it was deemed no longer necessary and of the least importance to users.
The last spring term release was published on 30 August 2012:
For the 2005/06 academic year, due to the transition of absence collection between the Absence in Schools Survey and the school census, absence information was published for secondary schools only as a National Statistics release.
Absence data for 2005/06 were not released on a termly basis as this was the first year of collection.
For academic years 1999/00 to 2004/05, annual pupil absence information was collected via the Absence in Schools Survey and published as an annual National Statistics release.
For academic years 1993/94 to 1998/99, annual pupil absence information was collected via the Absence in Schools Survey and published via Statistical bulletins. Links to all absence publications can be found in Annex C.
DfE monitors pupil absence levels using two key measures - overall absence rate and persistent absence (PA) rate.
These key measures are calculated for pupils who are of compulsory school age - ie aged between 5 and 15 as at the start of the academic year (31 August).
Absence information is reported as totals or rates across a period, usually by school term or academic year.
Overall absence is the aggregated total of all authorised and unauthorised absences.
Authorised absence is absence with permission from a teacher or other authorised school representative - including absences where a satisfactory explanation has been provided. For example, through illness.
Unauthorised absence is absence without permission from the school. This includes all unexplained or unjustified absences and arrivals after registration has closed.
For further information: 3.1 Overall absence methodology.
Persistent absence is when a pupil enrolment’s overall absence equates to 10% or more of their possible sessions.
For further information: 3.2 Persistent absence methodology.
Absence information is collected and disseminated at enrolment level rather than pupil level.
This means where a pupil has moved school throughout the year, theyll be counted more than once as they have recorded attendance and absence at more than one school.
This allows for schools to be held accountable for pupil absences, as the absence is attached to enrolments at a particular school, not the individual pupil.
All the enrolments at a school over the period in question are included in the absence measures, not just the pupils on roll at a particular date.
Schools only record absence for the period a pupil is on roll at their school.
The number of pupil enrolments is approximately 4% higher than the number of pupils.
Generally, the academic year is made up of three terms - autumn, spring and summer.
Each term has two parts (half-terms) which are usually separated by a half term break.
Since the 2012/13 academic year, pupil absence information has been collected for the full academic year (ie all six half terms).
However, prior to this absence information was collected for the first five half terms only, meaning absences in the second half of the summer term were not collected.
Since the 2012/13 academic year, DfE's key absence indicators have been based on the full academic year’s (ie six half terms) data.
However, as we're unable to rework time series tables or provide any historical six half term absence levels DfE continued to publish a full set of absence information for the first five half terms up to and including the 2013/14 academic year.
Following this, a single csv file based on data for five half terms has been published alongside the annual absence publications so longer term-time comparisons can still be made.
To account for high levels of study leave and other authorised absences for pupils aged 15 in the second half of the summer term, all possible sessions and absences relating to this period for 15 year olds (as at the start of the academic year) are removed prior to any analysis being undertaken and are not included in any published statistics.
| Academic year | Pupil numbers as at January each year1 | Enrolment numbers across full academic year | Percentage difference |
|---|---|---|---|
| 2012/13 | 6,230,420 | 6,477,725 | 4.0 |
| 2013/14 | 6,300,105 | 6,554,005 | 4.0 |
| 2014/15 | 6,381,940 | 6,642,755 | 4.0 |
| 2015/16 | 6,484,725 | 6,737,190 | 3.9 |
| 1 Pupils with a sole or dual main registration, aged between 5 and 15 who are not boarders as of the January school census each year. |
In published absence statistics, pupil enrolments who first enrolled at a school within the second half of the summer term are not included.
This is to ensure the same cohorts of enrolments are included in both the five and six half term absence measures.
DfE routinely publishes pupil absence information at national, local authority and school level - including breakdowns by pupil characteristics.
The autumn term absence publication provides high level information designed to give an early indication on absence levels and the effect of winter illness. This includes:
The combined autumn and spring term publication includes similar information to that of the autumn term. However, it also includes absence levels broken down by pupil:
The full academic year's absence publication includes combined absence # information for the autumn, spring and summer terms.
It’s the largest publication and includes similar breakdowns to that of the combined autumn and spring term publication (as outlined above) as well as persistent absence broken down by reason for absence and pupil characteristic.
Additional breakdowns included in this full year release relate to the:
In this publication, information is also provided at district level, based on Income Deprivation Affecting Children Index (IDACI) and by degree of rurality.
In addition, from 2015/16 onwards, characteristics include free school meal eligibility in the last six years.
The Income Deprivation Affecting Children Index (IDACI) is provided by the Department for Communities and Local Government (CLG).
The index measures the proportion of all children aged 0 to 15 living in income deprived families and is based on Lower-layer Super Output Areas (LSOAs) in England.
Each LSOA is given a rank between 1 and 32,844 where the LSOA with the rank of 1 is the most deprived LSOA and the LSOA with the rank of 32,844 is the most deprived.
IDACI is a subset of the Income Deprivation Domain of the Index of Multiple Deprivation 2015 which measures the proportion of the population in an area experiencing deprivation relating to low income.
The definition of low income used includes both those people that are out-of-work and those that are in work but who have low earnings (and who satisfy the respective means tests).
For further information about IDACI: English indices of deprivation 2015.
IDACI bands from 2014/15 are based on 2015 IDACI scores.
IDACI bands for 2010/11 to 2013/14 are based on 2010 IDACI scores and those for 2007/08 to 2009/10 are based on 2007 IDACI scores.
Care should be taken when comparing IDACI tables based on different IDACI scores.
The Rural and Urban Area Classification is a product of a joint project to produce a single and consistent classification of urban and rural areas. The project was sponsored by a number of government departments.
The rural and urban definitions classify output areas, wards and super output areas by aggregating the underlying hectare grid squares classifications for the measures of settlement size and sparsity.
Up to eight classes of output areas could be distinguished - four settlement types (urban, town and fringe, village, hamlet and isolated dwelling) in either a sparse or less sparse regional setting.
Absence data by degree of rurality from 2014/15 has been analysed based on the 2011 Rural and Urban Area Classification, whereas equivalent data for previous years was analysed based on the 2004 Rural and Urban Area Classification.
For further information about Rural and Urban Area Classification 2011: 2011 Rural-Urban Classification of Local Authorities and other geographies.
A full list of published absence breakdowns (as of the latest academic year's releases) is available in Annex D.
From 2015/16 onwards, published tables on characteristics breakdowns include figures for pupils with unclassified or missing characteristics information.
This represents a small proportion of all pupils and the figures should be interpreted with caution.
For some characteristics, like free school meals eligibility, pupils with unclassified or missing characteristics information have been found to have a low average number of sessions possible, which might explain more variability in absence rates which use the number of possible sessions as a denominator.
From the 2009/10 academic year, each National Statistics release has been accompanied by underlying data, including national, local authority and school level information.
Alongside the underlying data there's an accompanying document (metadata) which provides further information on the contents of these files.
This data is released under the terms of the Open Government License and is intended to meet at least 3 stars for Open Data.
Following the Consultation on improvements to pupil absence statistics, results published in October 2015, releases are now accompanied by time series underlying data, containing additional breakdowns and data from 2006/07 to the latest year.
This additional data is intended to provide users with all information in one place and give them the option of producing their own analysis.
The Code of Practice for Statistics requires reasonable steps are taken to ensure all published or disseminated statistics produced by DfE protect confidentiality.
To do this totals are rounded and small numbers are suppressed according to the following rules:
| Symbols used to identify this in published tables: | |
|---|---|
| 0 | Zero |
| x | Small number suppressed to preserve confidentiality |
| . | Not applicable |
| .. | Not available |
Pupil absence information is also available in the following publications:
In addition historical pupil absence data is available in the following discontinued publications:
DfE collects and reports on absence information from schools in England.
For information for Wales, Scotland and Northern Ireland:


ArcGIS Servers
Usage
- Type the URL of the REST endpoint of an ArcGIS Server. If the server follows the default naming convention,
you can just type the name of the server.
- Click the "Add Server" button.
A new list item will be created for this server and saved in the browser's local storage. This means that the next time you come to the page you will not have to re-enter the servers.
- If you want to remove a server from the list, click the "remove" link.
Get the Source Code from GitHub


How do I integrate Visual Basic 6.0 with Code Co-op?
First of
all, check to see if Code Co-op is recognized by VB. Go to Tools > Code Co-op > Check-out.
If Code Co-op is not listed:
- Close Visual Basic and edit your vbaddin.ini which is located in the Windows directory. Add the following entry under [Add-Ins32]: vbscc=3. Save the file. If you do not have this file, create and save it in your Windows directory.
If you see the Code Co-op menu item, yet cannot view the files do the following:
- Locate your VB project. Let's say it is located
in the folder 'c:\VBProject'.
- Run Code Co-op and select Project>New.
- Give it any name you want and, in the 'Where to find or create the project tree' edit
box, place 'c:\VBProject'. Code Co-op will ask you which files you want
to add to the project -- you may add *.vbp files as 'Other text', *.frm
as 'Binary' and source code files as 'Source'.
- Run VB and open the project located in the 'c:\VBProject' folder. VB will ask you if you want to add this project to Code Co-op -- answer yes. You will be presented with a list of files that VB wants to add to Code Co-op -- accept it. Now VB project is connected to Code Co-op project and inTools>Code Co-op menu you will see Check out and Check in items.


I am a new website deveoper, learning on my own through online courses. In the last year, I learned how to code using python in the Django framework. While I love how Django is designed to simplify building complex dynamic websites, it is a little too complicated for creating a personal site. Deploying it is a whole other thing.
I built this site using Jekyll and github pages, using a theme I borrowed from Konstantinos CHorianopoulos on Github and customized for my needs. It was originally a personal card but I added pages and navigation to link them together to showcase all the things I am doing at the moment.
Building a site using Jekyll is a lot easier and the site loads faster once you test it on a browser compared to Django. There are components that I do miss from Django but for a simple personal website, I found that Jekyll is more suitable.


Purchase
Confirmation
Commodity:
{{myForm.commodityName}}
Grade:
{{myForm.gradeName}}
COMMODITY PURCHASE AND DEFERRED DELIVERY AGREEMENT {{myForm.CWTDel | number:2}}
Between Rudy Agro Ltd and:
Seller :
{{ myForm.personFarmType =='Person' ? growerDetails.firstName +" "+ growerDetails.lastName : myForm.farmName}}
Address :
{{growerDetails.addresses[0].street}}
{{(growerDetails.addresses[0].town+' '+growerDetails.addresses[0].country+' '+growerDetails.addresses[0].province)}}
{{growerDetails.addresses[0].postal}}
Phone : {{growerDetails.phone2}}
Email : {{growerDetails.email}}
Date:
{{(myForm.backDate|date) ||(myForm.createdAt|date:'MM/dd/yyyy')}}
Contract #: {{myForm.contractNumber}}
Commodity: {{myForm.commodityName}}
Grade:
{{myForm.gradeName}}
Crop Year: {{myForm.cropYear}}
Delivery Point: {{myForm.deliveryPoint}}
Contracted
Quantity: {{myForm.contractQuantity | number:2}}
{{myForm.quantityUnit}} NET
Delivery Period: {{myForm.shipmentPeriodFrom}} -
{{myForm.shipmentPeriodTo}}
Specifications:
{{myForm.specifications}}
Purchase Price:
{{myForm.price | number:4}} / {{myForm.priceUnit}} C$
Payment Term:
{{myForm.paymentTerms}}
Handling Tariff:
A handling tariff will be levied against all deliveries
- $8.00/MT on Lentils, Chick Peas, Edible Beans,Canaryseed, Marrowfat Peas, $3.50/mt on all other
Peas, Flax and Canola
Settlement
Instructions: {{myForm.settlementInstructions}}
Other
Conditions:
{{myForm.otherConditions}}
-
The Seller will deliver, at its own expense and in good and dry condition, the Commodity to the named
delivery point, on a date to be specified by Rudy Agro on 5 day’s notice to the Seller during the
delivery period. The Seller warrants free and clear title to the Commodity and that the Commodity is
not, and will not be, encumbered by contract or otherwise. The Seller shall not be entitled to receive a
higher price than that specified above even if, following delivery, the Commodity is graded higher than
the grade stated above.
-
The Seller shall bear all costs of delivery to the named delivery point as aforesaid, and all risk in
relation to the Commodity until completion of its delivery to Rudy Agro.
-
Payment shall be made on the basis of weight net of dockage less the applicable handling tariff.
-
Upon delivery of the Commodity, Rudy Agro shall determine the weight/quantity, grade, dockage and
moisture content in accordance with procedures and official standards of the Canadian Grain Commission.
It is understood that the purchase price is basis the commodity being delivered “dry” in accordance to
the CGC and if product is received at higher moisture i.e. “tough” or “damp” it may result in additional
charges or rejection of the load at the Sellers expense.In the event of a disagreement, the parties
shall forward a suitable representative sample to the Canadian Grain Commission, and the results thereof
shall be conclusive and binding.
-
(a) The Seller shall be responsible for all loss, damage and expense incurred by Rudy Agroarising
directly or indirectly from the failure or neglect of the Seller, whether within or beyond its control,
including as a result of any acts of God, to perform this agreement or any provision of it, including
but not limited to the delivery of Commodity of a lesser quality. As well, the Seller agrees that the
Commodity does not constitute “specific goods” as defined in The Sale of Goods Act.
(b) In the event of any such failure or neglect, Rudy Agro shall be entitled to pursue all remedies
available under law against the Seller, including all losses and expenses incurred by Rudy Agro in
relation any default or breach by the Seller of any contractual arrangements between it and a 3rd party
or parties inrelation to the Commodity, due to Rudy replacing or attempting to replace the Commodity
from other sources and/or from Rudy accepting late and/or partial delivery from the Seller, as Rudy Agro
may in its sole discretion elect.
-
Rudy Agro may set off against, and deduct from, any payment to the Seller for the Commodity, any
indebtedness of the Seller to Rudy Agro.
-
Time shall be essence of this contract, and any extension thereof or other forbearance by Rudy Agro
hereunder shall not constitute or be construed as a waiver of its right to require strict performance of
all other provisions of this agreement.
-
Any notice given under the terms of this agreement shall be conclusively deemed to have been properly
given and received if provided to a party by any one of the mailing, facsimile or email addresses
specified at the beginning of this agreement for the party to whom the notice is being provided.
-
This contract shall be deemed to have been made in the Province of Saskatchewan and shall be interpreted
according to the laws and by the courts of Saskatchewan.
-
This agreement forms the entire contract between the parties and no modification or variation is valid
unless in writing signed by the Seller and Rudy Agro
-
The Seller acknowledges having received good and valuable consideration for its entry into this
agreement, including securing a price certain for the Commodity, and also that Rudy Agro shall incur
risk, effort and expense in reliance on this agreement.
Accepted for Seller
Accepted For Buyer


Maps and Navigation (C++)
Maps and Navigation provides C++ utilities for geocoding (finding a geographic coordinate from a street address) and navigation (including driving and walking directions).
Currently it is not possible to interact with maps via C++. Mapping applications must use the Maps and Navigation (QML) API.
Geocoding
In C++, an address-to-coordinate query is performed using the geocode() method of the QGeoCodingManager class. For coordinate-to-address queries, the reverseGeocode() method is available on the same class. Instances of QGeoCodingManager are available via QGeoServiceProvider.
Key Classes
| QGeoServiceProvider | Provides a QGeoCodingManager instance ready for use. |
| QGeoCodingManager | Accepts queries and produces QGeoCodeReply objects. |
| QGeoCodeReply | Contains the results of a geocoding query. |
Navigation
In C++, a route query is performed using the calculate() method of the QGeoRoutingManager class. The returned route reply can contain multiple routes to the same destination.
Key Classes
| QGeoServiceProvider | Provides a QGeoCodingManager instance ready for use. |
| QGeoRoutingManager | Accepts queries and produces QGeoRouteReply objects. |
| QGeoRouteReply | Contains the results of a routing query. |
| QGeoRoute | Contains information about a route. |


--- layout: archive title: Zulip Chat Archive permalink: /stream/113488-general/topic/introduce.20implication.html ---
Beginner question: is there an intro command for simple implication, like iff.intro for equivalence? I somehow can't find it in the manual
A lambda expression does that. λ x : t, (s : u)
has type t -> u
Ok, I see. I'm trying to solve the simple exercise example : (∃ x : α, r) → r := sorry
, but I just can't find the right notation. Would anyone mind telling me the answer?
Do you want to use term mode or tactic mode? With or without mathlib?
Assuming r
is a proposition (of type Prop
) then the following is a short way to prove it:
example {α : Type} {r : Prop} : (∃ x : α, r) → r := λ⟨x, h⟩, h
The λ⟨x, h⟩
introduces a variable x : α
and h : r
(so that together, ⟨x, h⟩ : ∃ x : α, r
), and then the proof of r
is h
.
This doesn't work if r
is not a proposition.
Slightly longer, but without the ⟨x, h⟩
brackets:
example {α : Type} {r : Prop} : (∃ x : α, r) → r := λ prf, exists.elim prf (λ x h, h)
Here we call exists.elim prf
to eliminate the existential quantifier.
@Floris van Doorn : thanks. @Johan Commelin : I'm just getting started, so I'm not sure about those distinctions
If your background is in CS then you might want to start with term mode like Floris was doing. If you background is in maths then you might want to learn tactic mode first
Yes, I also wanted to give you an example of the proof in tactic mode, but I had to run:
example {α : Type} {r : Prop} : (∃ x : α, r) → r := begin intro prf, cases prf with x h, exact h end
Probably the best way to learn more is to look at relevant parts of theorem proving in Lean
That is an exercise from "Theorem proving in Lean", in that chapter they are showing answers in term mode.
Btw, is there a reference handbook/file of sorts that lists all possible "commands" for Lean?
The command #help commands
lists them, with a short description.
But those are just the top-level commands, like def
and import
and so on
There's also the reference manual, which may not be 100% up to date, but tries to document things like this. https://leanprover.github.io/reference/
Thanks, guys
{% endraw %}Last updated: Apr 24 2020 at 19:02 UTC


Duke scores 17 to lift Providence past St. Peter's 68-47
by EndPlayPROVIDENCE, R.I. (AP) - David Duke had 17 points and six assists as Providence romped past St. Peter's 68-47 on Saturday.
Alpha Diallo had 15 points and nine rebounds for Providence (3-1). Luwane Pipkins added seven assists.
Matthew Lee had 10 points for the Peacocks (0-2). Fousseyni Drame added seven rebounds.
Providence faces Merrimack at home on Tuesday. St. Peter's plays Wagner at home on Wednesday.
___
For more AP college basketball coverage: https://apnews.com/Collegebasketball and http://twitter.com/AP_Top25
___
This was generated by Automated Insights, http://www.automatedinsights.com/ap, using data from STATS LLC, https://www.stats.com


OneSignal
The OneSignal plugin is an client implementation for using the OneSignal Service. OneSignal is a simple implementation for delivering push notifications.
Requires Cordova plugin: onesignal-cordova-plugin
. For more info, please see the OneSignal Cordova Docs.
Repo: https://github.com/OneSignal/OneSignal-Cordova-SDK
Installation
- Install the Cordova and Ionic Native plugins:
$ ionic cordova plugin add onesignal-cordova-plugin $ npm install --save @ionic-native/onesignal
- Add this plugin to your app's module
Supported platforms
- Android
- iOS
- Windows
- FireOS
Usage
import { OneSignal } from '@ionic-native/onesignal';
constructor(private oneSignal: OneSignal) { }
...
this.oneSignal.startInit('b2f7f966-d8cc-11e4-bed1-df8f05be55ba', '703322744261');
this.oneSignal.inFocusDisplaying(this.oneSignal.OSInFocusDisplayOption.InAppAlert);
this.oneSignal.handleNotificationReceived().subscribe(() => {
// do something when notification is received
});
this.oneSignal.handleNotificationOpened().subscribe(() => {
// do something when a notification is opened
});
this.oneSignal.endInit();
Instance Members
OSInFocusDisplayOption
constants to use in inFocusDisplaying()
startInit(appId, googleProjectNumber)
Start the initialization process. Once you are done configuring OneSignal, call the endInit
function.
| Param | Type | Details |
|---|---|---|
| appId |
string
|
Your OneSignal app id |
| googleProjectNumber |
string
|
ANDROID - your Google project number; only required for Android GCM/FCM pushes. |
Returns: any
handleNotificationReceived()
Callback to run when a notification is received, whether it was displayed or not.
Returns: Observable<OneSignalReceivedNotification>
handleNotificationOpened()
Callback to run when a notification is tapped on from the notification shade (ANDROID) or notification center (iOS), or when closing an Alert notification shown in the app (if InAppAlert is enabled in inFocusDisplaying).
Returns: Observable<OneSignalOpenedNotification>
iOSSettings(settings)
iOS - Settings for iOS apps
| Param | Type | Details |
|---|---|---|
| settings |
kOSSettingsKeyAutoPrompt: boolean = true Auto prompt user for notification permissions. kOSSettingsKeyInAppLaunchURL: boolean = false Launch notifications with a launch URL as an in app webview. |
Returns: any
endInit()
Must be called after startInit
to complete initialization of OneSignal.
Returns: any
getTags()
Retrieve a list of tags that have been set on the user from the OneSignal server.
Quirk: You must wait for getTags
to resolve before calling it again, as the plugin will only process the last method call and discard any previous ones.
Returns: Promise<any>
Returns a Promise that resolves when tags are recieved.
getIds()
Lets you retrieve the OneSignal user id and device token. Your handler is called after the device is successfully registered with OneSignal.
Returns: Promise<Object>
Returns a Promise that resolves if the device was successfully registered.
userId {string} OneSignal userId is a UUID formatted string. (unique per device per app)
pushToken {string} A push token is a Google/Apple assigned identifier(unique per device per app).
sendTag(Key, Value)
Tag a user based on an app event of your choosing so later you can create segments on onesignal.com to target these users. Recommend using sendTags over sendTag if you need to set more than one tag on a user at a time.
| Param | Type | Details |
|---|---|---|
| Key |
string
|
of your choosing to create or update. |
| Value |
string
|
to set on the key. NOTE: Passing in a blank String deletes the key, you can also call deleteTag. |
sendTags(Pass)
Tag a user based on an app event of your choosing so later you can create segments on onesignal.com to target these users. Recommend using sendTags over sendTag if you need to set more than one tag on a user at a time.
| Param | Type | Details |
|---|---|---|
| Pass |
string
|
a json object with key/value pairs like: {key: "value", key2: "value2"} |
deleteTag(Key)
Deletes a tag that was previously set on a user with sendTag
or sendTags
. Use deleteTags
if you need to delete more than one.
| Param | Type | Details |
|---|---|---|
| Key |
string
|
to remove. |
deleteTags(Keys)
Deletes tags that were previously set on a user with sendTag
or sendTags
.
| Param | Type | Details |
|---|---|---|
| Keys |
Array<string>
|
to remove. |
registerForPushNotifications()
Call this when you would like to prompt an iOS user to accept push notifications with the default system prompt.
Only works if you set kOSSettingsAutoPrompt
to false
in iOSSettings
enableVibrate(false)
Warning: Only applies to Android and Amazon. You can call this from your UI from a button press for example to give your user’s options for your notifications.
By default OneSignal always vibrates the device when a notification is displayed unless the device is in a total silent mode. Passing false means that the device will only vibrate lightly when the device is in it’s vibrate only mode.
| Param | Type | Details |
|---|---|---|
| false |
boolean
|
to disable vibrate, true to re-enable it. |
enableSound(false)
Warning: Only applies to Android and Amazon. You can call this from your UI from a button press for example to give your user’s options for your notifications.
By default OneSignal plays the system’s default notification sound when the device’s notification system volume is turned on. Passing false means that the device will only vibrate unless the device is set to a total silent mode.
| Param | Type | Details |
|---|---|---|
| false |
boolean
|
to disable sound, true to re-enable it. |
inFocusDisplaying(displayOption)
Setting to control how OneSignal notifications will be shown when one is received while your app is in focus. By default this is set to inAppAlert, which can be helpful during development.
| Param | Type | Details |
|---|---|---|
| displayOption |
DisplayType
|
Returns: any
setSubscription(enable)
You can call this method with false to opt users out of receiving all notifications through OneSignal. You can pass true later to opt users back into notifications.
| Param | Type | Details |
|---|---|---|
| enable |
boolean
|
postNotification(Parameters)
| Param | Type | Details |
|---|---|---|
| Parameters |
notificationObj
|
see POST documentation |
Returns: Promise<any>
Returns a Promise that resolves if the notification was send successfully.
promptLocation()
Prompts the user for location permission to allow geotagging based on the “Location radius” filter on the OneSignal dashboard.
syncHashedEmail(email)
| Param | Type | Details |
|---|---|---|
string
|
setLogLevel(contains)
Enable logging to help debug if you run into an issue setting up OneSignal. The logging levels are as follows: 0 = None, 1= Fatal, 2 = Errors, 3 = Warnings, 4 = Info, 5 = Debug, 6 = Verbose
The higher the value the more information is shown.
| Param | Type | Details |
|---|---|---|
| contains |
loglevel
|
two properties: logLevel (for console logging) and visualLevel (for dialog messages) |
OSNotification
| Param | Type | Details |
|---|---|---|
| isAppInFocus |
boolean
|
Was app in focus. |
| shown |
boolean
|
Was notification shown to the user. Will be false for silent notifications. |
| androidNotificationId |
number
|
ANDROID - Android Notification assigned to the notification. Can be used to cancel or replace the notification. (optional) |
| payload |
OSNotificationPayload
|
Payload received from OneSignal. |
| displayType |
OSDisplayType
|
How the notification was displayed to the user. Can be set to |
| groupedNotifications |
OSNotificationPayload[]
|
ANDROID - Notification is a summary notification for a group this will contain all notification payloads it was created from. (optional) |
| app_id |
string
|
(optional) |
| contents |
any
|
|
| headings |
any
|
(optional) |
| isIos |
boolean
|
(optional) |
| isAndroid |
boolean
|
(optional) |
| isWP |
boolean
|
(optional) |
| isWP_WNS |
boolean
|
(optional) |
| isAdm |
boolean
|
(optional) |
| isChrome |
boolean
|
(optional) |
| isChromeWeb |
boolean
|
(optional) |
| isSafari |
boolean
|
(optional) |
| isAnyWeb |
boolean
|
(optional) |
| included_segments |
string[]
|
(optional) |
| excluded_segments |
string[]
|
(optional) |
| include_player_ids |
string[]
|
(optional) |
| include_ios_tokens |
string[]
|
(optional) |
| include_android_reg_ids |
string[]
|
(optional) |
| include_wp_uris |
string[]
|
(optional) |
| include_wp_wns_uris |
string[]
|
(optional) |
| include_amazon_reg_ids |
string[]
|
(optional) |
| include_chrome_reg_ids |
string[]
|
(optional) |
| include_chrome_web_reg_ids |
string[]
|
(optional) |
| app_ids |
string[]
|
(optional) |
| tags |
any[]
|
(optional) |
| ios_badgeType |
string
|
(optional) |
| ios_badgeCount |
number
|
(optional) |
| ios_sound |
string
|
(optional) |
| android_sound |
string
|
(optional) |
| adm_sound |
string
|
(optional) |
| wp_sound |
string
|
(optional) |
| wp_wns_sound |
string
|
(optional) |
| data |
any
|
(optional) |
| buttons |
any
|
(optional) |
| small_icon |
string
|
(optional) |
| large_icon |
string
|
(optional) |
| big_picture |
string
|
(optional) |
| adm_small_icon |
string
|
(optional) |
| adm_large_icon |
string
|
(optional) |
| adm_big_picture |
string
|
(optional) |
| chrome_icon |
string
|
(optional) |
| chrome_big_picture |
string
|
(optional) |
| chrome_web_icon |
string
|
(optional) |
| firefox_icon |
string
|
(optional) |
| url |
string
|
(optional) |
| send_after |
string
|
(optional) |
| delayed_option |
string
|
(optional) |
| delivery_time_of_day |
string
|
(optional) |
| android_led_color |
string
|
(optional) |
| android_accent_color |
string
|
(optional) |
| android_visibility |
number
|
(optional) |
| content_available |
boolean
|
(optional) |
| amazon_background_data |
boolean
|
(optional) |
| template_id |
string
|
(optional) |
| android_group |
string
|
(optional) |
| android_group_message |
any
|
(optional) |
| adm_group |
string
|
(optional) |
| adm_group_message |
any
|
(optional) |
| ttl |
number
|
(optional) |
| priority |
number
|
(optional) |
| ios_category |
string
|
(optional) |
OSLockScreenVisibility
| Param | Type | Details |
|---|---|---|
| Public |
1
|
Fully visible (default) |
| Private |
0
|
Contents are hidden |
| Secret |
-1
|
Not shown |
OSDisplayType
| Param | Type | Details |
|---|---|---|
| None |
0
|
notification is silent, or inFocusDisplaying is disabled. |
| InAppAlert |
1
|
(DEFAULT) - native alert dialog display. |
| Notification |
2
|
native notification display. |
OSNotificationPayload
| Param | Type | Details |
|---|---|---|
| notificationID |
string
|
OneSignal notification UUID. |
| title |
string
|
Title of the notification. |
| body |
string
|
Body of the notification. |
| additionalData |
any
|
Custom additional data that was sent with the notification. Set on the dashboard under Options > Additional Data or with the 'data' field on the REST API. (optional) |
| smallIcon |
string
|
ANDROID - Small icon resource name set on the notification. (optional) |
| largeIcon |
string
|
ANDROID - Large icon set on the notification. (optional) |
| bigPicture |
string
|
ANDROID - Big picture image set on the notification. (optional) |
| smallIconAccentColor |
string
|
ANDROID - Accent color shown around small notification icon on Android 5+ devices. ARGB format. (optional) |
| launchUrl |
string
|
URL to open when opening the notification. (optional) |
| sound |
string
|
Sound resource to play when the notification is shown. |
| ledColor |
string
|
ANDROID - Devices that have a notification LED will blink in this color. ARGB format. (optional) |
| lockScreenVisibility |
OSLockScreenVisibility
|
(optional) |
| groupKey |
string
|
ANDROID - Notifications with this same key will be grouped together as a single summary notification. (optional) |
| groupMessage |
string
|
ANDROID - Summary text displayed in the summary notification. (optional) |
| actionButtons |
OSActionButton[]
|
List of action buttons on the notification. |
| fromProjectNumber |
string
|
ANDROID - The Google project number the notification was sent under. (optional) |
| backgroundImageLayout |
OSBackgroundImageLayout
|
ANDROID - If a background image was set this object will be available. (optional) |
| priority |
number
|
(optional) |
| rawPayload |
string
|
List of action buttons on the notification. |
OSActionButton
| Param | Type | Details |
|---|---|---|
| id |
string
|
Id assigned to the button. |
| text |
string
|
Text show on the button to the user. |
| icon |
string
|
ANDROID - Icon shown on the button. |
OSBackgroundImageLayout
| Param | Type | Details |
|---|---|---|
| image |
string
|
Image URL or name used as the background image. |
| titleTextColor |
string
|
Text color of the title on the notification. ARGB Format. |
| bodyTextColor |
string
|
Text color of the body on the notification. ARGB Format. |
OSNotificationOpenedResult
| Param | Type | Details |
|---|---|---|
| action |
*/
actionID?: string;
}
|
|
| notification |
OSNotification
|
OSActionType
| Param | Type | Details |
|---|---|---|
| Opened |
0
|
|
| ActionTake |
1
|


{% load static %}
Semester: {{ section.0.semester }} {{ section.0.year }}
Type: {{ section.0.section_type }} ({{section.0.num_type}})
start time: {{ section.0.start_time }}
end time: {{ section.0.end_time }}
capacity: {{ section.0.capacity }}
room: {{ section.0.room }}
Days: {{ section.1 }}


--- layout: post title: World Hunger {Infographic} date: 2010-05-15 03:32:00.000000000 -05:00 comments: true categories: - Infographic published: true ---
As a topic that is near and dear to my heart, this infographic prepared by the fine folks over at stripes39.com is absolutely interesting.


M:PureDI.Tree.ObjectTree.CreateObjectTree(System.ValueTuple{System.Type,System.String,System.String},PureDI.Tree.CreationContext,PureDI.IOCCDiagnostics,PureDI.Tree.BeanReferenceDetails,PureDI.BeanScope)
see documentation for CreateAndInjectDependencies
beanId
the type + beanName for which a bean is to be created.
The bean will not necessarily have the type passed in as this
may be a base class or interface (constructed generic type)
from which the bean is derived
beanReferenceDetails
provides a context to the bean that
can be displayed in diagnostic messages - currently not used for
anything else
mapObjectsCreatedSoFar
for all beans instantiated to this point
maps the name of the class or struct of
the object to the instance of the object.
fieldOrPropertyInfo1
used to determine the scope of the bean to be created


{{student. name | uppercase}} {{student.surname}}
2.5">Good Student who get grade {{student.gpa | number:'1.2-2'}}
Bad Student who get grade {{student.gpa | number:'1.2-2'}}


South Africa beat England to lift Rugby World Cup
Springboks secure their third World Cup trophy after dominating the final.
South Africa have defeated England 32-12 to win the 2019 Rugby World Cup at the Yokohama International Stadium in Japan.
Tries by wingers Makazole Mapimpi and Cheslin Kolbe and the goalkicking of Handre Pollard earned South Africa their third Rugby World Cup title on Saturday as the fly-half kicked 22 points to secure a 32-12 victory over an error-strewn England.
More:
South Africa led 12-6 at half time through four Pollard penalties with Owen Farrell replying for an England team who had been overpowered in the scrum, having lost injured prop Kyle Sinckler after three minutes, and who committed a series of handling errors.
South Africa, playing with far more ambition than in their semi-final win over Wales, kept up the pressure in the second half as England struggled to build momentum and Pollard nudged them 18-12 ahead after an hour.
The Springboks then scored their first try in three World Cup finals when Mapimpi broke clear in the 66th minute, chipped ahead and collected the ball back from Lukhanyo Am, and recalled winger Kolbe then blasted through to put the gloss on a deserved win.
After the final whistle, Springboks captain Siya Kolisi thanked all South Africans, from the people on the farms to those in the townships and on the streets.
"We can achieve anything if we work together as one," said Kolisi, who last year became the first black player appointed as Springboks captain.
The significance of Kolisi leading the team to victory was not lost on the supporters who gathered at Johannesburg's fan zones to watch the match.
"This win means a lot to us. This is the most amount of black players we have had in a World Cup squad. All the players in that squad deserve to be in the squad. They have united the whole country. Everyone is behind them. They have given us something to smile about," a supporter told Al Jazeera.
Reporting from a fan zone in Johannesburg, Al Jazeera's Fahmida Miller, said the team's supporters were "very excited".
"They are thrilled to see the 'Boks' win. They believe their team has deserved the trophy. Celebrations will continue for long."
The win also ensured the Springboks became the first team to lose a game and rebound to win the title, having lost their tournament-opening match last month to the two-time champion All Blacks of New Zealand in the pool stage.


Plaid API Settings
@@TODO: name? environment?
Client ID:
Public Key:
Secret:
Create
result...
fincap by Dan Connolly


Accounts
Users
User Roles
Groups
Categories
Languages
Languages List
Labels
Plugins
Crowd Sourcing
Ideas
Comments
Configure
eMail Management
Smtp
Senders
Avatar
Dynamic Web Forms
Message List
Configuration
Message Types
My Portal
Profile Management
Your Profile
Profiles
Profile Types
Forum
Forum Sections
Forum Configuration


More...
|
| virtual bool | AutoLoad [get, set] |
| | True to automatically load the related store from a remote source when instantiated. Defaults to false. More...
|
| |
| virtual string | FilterProperty [get, set] |
| | Optionally overrides the default filter that is set up on the associated Store. If this is not set, a filter is automatically created which filters the association based on the configured foreignKey. See intro docs for more details. Defaults to undefined More...
|
| |
| virtual string | ForeignKey [get, set] |
| | The name of the foreign key on the associated model that links it to the owner model. Defaults to the lowercased name of the owner model plus "_id", e.g. an association with a where a model called Group hasMany Users would create 'group_id' as the foreign key. More...
|
| |
| virtual string | Name [get, set] |
| | The name of the function to create on the owner model to retrieve the child store. If not specified, the pluralized name of the child model is used. More...
|
| |
| Store | StoreConfig [get] |
| | Optional configuration object that will be passed to the generated Store. Defaults to undefined. More...
|
| |
| virtual string | AssociationKey [get, set] |
| | The name of the property in the data to read the association from. Defaults to the name of the associated model. More...
|
| |
| virtual string | PrimaryKey [get, set] |
| | The name of the primary key on the associated model. In general this will be the Ext.data.Model.idProperty of the Model. Defaults to 'id' More...
|
| |
| virtual string | Model [get, set] |
| | The string name of the model that is being associated with. Required More...
|
| |
| ReaderCollection | Reader [get] |
| | A special reader to read associated data More...
|
| |
◆ operator HasManyAssociation.Builder()
◆ AutoLoad
| virtual bool Ext.Net.HasManyAssociation.Config.AutoLoad |
|
getset |
True to automatically load the related store from a remote source when instantiated. Defaults to false.
◆ FilterProperty
| virtual string Ext.Net.HasManyAssociation.Config.FilterProperty |
|
getset |
Optionally overrides the default filter that is set up on the associated Store. If this is not set, a filter is automatically created which filters the association based on the configured foreignKey. See intro docs for more details. Defaults to undefined
◆ ForeignKey
| virtual string Ext.Net.HasManyAssociation.Config.ForeignKey |
|
getset |
The name of the foreign key on the associated model that links it to the owner model. Defaults to the lowercased name of the owner model plus "_id", e.g. an association with a where a model called Group hasMany Users would create 'group_id' as the foreign key.
◆ Name
| virtual string Ext.Net.HasManyAssociation.Config.Name |
|
getset |
The name of the function to create on the owner model to retrieve the child store. If not specified, the pluralized name of the child model is used.
◆ StoreConfig
| Store Ext.Net.HasManyAssociation.Config.StoreConfig |
|
get |
Optional configuration object that will be passed to the generated Store. Defaults to undefined.
The documentation for this class was generated from the following file:
- HasManyAssociationConfig.cs


the and vaccine are vaccines protein with []. for that SARS-CoV virus against coronavirus respiratory DNA immune antibodies have been neutralizing viral syndrome acute which {background proteins also from responses SARS can response spike The has inactivated mRNA margin mice Virol. [], cells not severe {border-style SARS-CoV- antibody [,]. based but host human immunity infection px;} this was #ffffff;} cell clinical other development induce reported vector MERS-CoV efficacy protective such T-cell induced recombinant CoV RBD attenuated candidate gene its target their they candidates different effective humoral novel nucleocapsid production were could expression into similar subunit there these used various COVID- cellular safety MHC animal developing pathogen safe vaccination vaccinia vectors Further Immunol. RNA Res. associated because both disease domain expressed induces innate live may mouse px; some specific study very viruses well {font-family Med. SARS-CoV, WKV adenovirus antigen cytotoxic demonstrated efficient expressing font-size high highly humans including model most only potential receptor replication studies thus BALB/c Dis. However, Infect. Recombinant Rev. SAR-CoV- able action any binding case class double; elicit eliciting encoding epitopes form immunogenicity infectious like might new possible research strategies strong structural tract trial two whole Biophys. Commun. East Elsevier Inactivated Sci. These Vaccine []]. act additional administration after another antigens available border-color border-width causing centre common compared coronavirus: during effects elicited encoded endogenous fragments genes genome hepatitis i.e. immunization inducing infected injected lower many mediated membrane models modified need nucleic number plasmid potent prepared present produced protection proteins, shown significant solid; strain time using vaccine, where yet {font-style {font-weight (SARS) Acad. Ankara Besides Biol. Coronavirus Due Engl. Further, Gen. MVA Microbiol. Natl. Phase Since Vaccines [,] [[], acid adenoviral all antigenic antiviral approach approaches appropriate attractive being bold coding constructs courier; deletion develop diseases efficiently either em; emerging envelope epidemics epitope field first free further generate generation global infections less limitations long long-term make makes making memory more nasal order outbreak pathogens patients phase pneumonia prevent prone prophylactic pt;} recent reduced requires resource response, response. results reversion review risk route, serum several site stable strains suitable symptoms targets tested than therapeutic thereby through trials. upper vaccinated vaccines: virulence virulent virus: vivo without


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JERRY MAGUIRE Copyright 1996 D & S Associates
Tom Cruise is Jerry Maguire, a hot shot sports agent with 72 clients who's yanked back to humanity by the son of a hockey player suffering his 4th concussion. Jerry writes a mission statement for his company, SMI, recommending providing more care for client's welfare by serving fewer clients and bringing in less money. This action, while secretly admired by many, promptly gets him fired. One accountant, single mom Dorothy Boyd played by newcomer Rene Zellweger, is inspired to follow him. Only one client, Cuba Gooding Jr.'s Rod Tidwell, a second tier wide receiver for the Arizona Cardinals, remains.
LAURA:
Simply put, "Jerry Maguire" is the best commercial Hollywood film I've seen so far this year. Cameron Crowe has written and directed a story that operates on many levels and rings 100% true on every one of them.
"Jerry Maguire" is a romance, the story of a man going to the bottom from the top professionally and back again, the story of a man finding himself, a view into the building of a friendship and those friends teaching each other life lessons and the story of a single mom following her heart while raising a son. It IS a comedy, but it's a comedy based on real human emotion.
Tom Cruise gives his best performance to date here - he hasn't been this appealing since "Risky Business" broke him into our consciousness. I haven't seen all his competition yet, but I hope he gets Academy recognition for this role - he really deserves it. He's sexy, charming, frustrated, caring, conflicted, passionate and honorable. Rene Zellweger is a find as Dorothy, the woman who believes she's 'taken advantage' of Maguire at his low point. The two have real chemistry together. Bonnie Hunt is fun as Laurel, Dorothy's sister, who provides unwished for practical advice all the while knowing that love is blind. Cuba Gooding Jr. matches Cruise toe-to-toe as the washed up footballer needing an attitude adjustment. Regina King is wonderful as his loving (pregnant) wife Marcy - the two have a great marriage and it shows (glows?). Newcomer Jonathan Lipnicki as Ray Boyd, Dorothy's son, is quirkily adorable, although also responsible for one of the film's few shortfallings. It's so obvious that Lipnicki adores Tom Cruise that he's clearly not acting and it draws one out of the film.
Technically, this is a quality production all around. I particularly liked the soundtrack, which uses snippets of many varied songs to good effect. When Cruise cruises the radio dial trying to find something to match his mood and settles in with and bellows along with "Free Falling", it's infectious!
Cuba Gooding Jr.'s motto is 'Show me the money!'. Well, I've been shown - I've seen "Jerry Maguire."
A
ROBIN:
It stuns me that I'm saying that "Jerry Maguire" is the best thing to come out of Hollywood (with the exception of my personal favorite "The Hunchback of Notre Dame") in 1996. There. I said that about a film starrung Tom Cruise.
Cameron Crowe has written a first-class screenplay and couple it with a professional and talented cast and crew. His "Jerry Maguire" is an old-fashioned romantic and sports comedy, with a multi-threaded story that dovetails nicely in its several directions, coming nicely together in the end. I haven't seen this kind of crafting, except from the independent film arena, in a long, long time. Especially from Hollywood.
Tom Cruise give his best performance, yet, as the sports agent who develops a conscience and heart. Jerry Maguire learns the qualities of loyalty, integrity, friendship and love and Cruise does an admirable job of portraying this man. Both Maguire and Cruise are charmers.
Cuba Gooding JR., as pro footbal jock, Rod Tidwell, is funny and flashy and is a major contributor to the humor and quality of "Jerry Maguire". When he gets, finally, what he wants, you feel good for him and his wife, played strongly and effectively by Regina King.
Newcomers Renee Zellweger and Jonathan Lipnicki as Cruise' romantic interest, Dorothy and her little boy, Ray, are solid, if not exceptional. Crowe uses little Jonathan Lipnicki to very good advantage, while avoiding overwhelming you with overt cuteness. (For example, one of the lines to come from the moppet is, "Do you know the human head weighs eight pounds?" Not typical cute kid dialog.
The rest of the cast, led by Bonnie Hunt, do a good job of keeping the background characters full and three dimensional. Like real people.
My only complaint is that, toward the end, as Jerry and Dorothy face their romantic crisis, things drag a little. Fortunately, it picks itself up quickly and finishes with a flourish.
"Jerry Maguire" is my first place recommendation for your holiday movie going.
A-
D&S Associates - Electronic Publishers Webmasters of Neponset.Com http://www.neponset.com voicemail:<PHONE_NUMBER> BBS:<PHONE_NUMBER> Visit "Reeling" at http://www.neponset.com/reeling.
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


UP5 - Gyro Drift
Overview
Estimates the gyro drift by checking against a turtlebot mounted kinect
(fake laser) that is pointed at a wall
Usage
- Place the robot in front of a wall.
- Configure the rotational speed.
- Press start.
- Scan error angle (gyro vs laser) is plotted on the graph.


--- layout: post status: publish published: true title: Success in 2011 Hinges on Injuries author: display_name: Corey Fineran login: Corey email<EMAIL_ADDRESS>url: '' author_login: Corey author_email<EMAIL_ADDRESS>wordpress_id: 3701 wordpress_url: http://ivyenvy.com/?p=3701 date: '2011-02-04 06:10:58 +0000' date_gmt: '2011-02-04 12:10:58 +0000' categories: - The Cubs - injuries tags: [] comments: - id: 2590 author: Ryan author_email<EMAIL_ADDRESS>author_url: '' date: '2011-02-16 20:10:53 +0000' date_gmt: '2011-02-17 02:10:53 +0000' content: "\"battling the Pirates to stay out of the cellar\" ... That's a scary line...we'll have to discuss this with Morchauser\r\n\r\nMeehan" ---
I realize that the title of this post is a bit of a cliche. That statement is true for every team in baseball. There are 2 or 3 players on every team that must, for the most part, stay healthy for the team to compete for their division title. The difference between that type of situation and the 2011 Cubs is if the Cubs stay healthy, they will MAYBE compete for the division. If they don't stay healthy, come September, they could easily be battling the Pirates to stay out of the cellar.
The Cubs are a much younger team than what we have seen for a number of years. If injuries do happen (and they will), these young and inexperienced players will be called on to step up. Over the next week or two, I will look at each position on the team and identify the weak spots in the line-up in regards to injuries and depth.


DfE enquiries
Central newsdesk 020 7783 8300
General enquiries 0370 000 2288
Press release
Great Coates Primary School to be rebuilt through the government’s £4.4 billion rebuilding programme.
Pupils at a Grimsby primary school will bury a time capsule today (2 October) to mark the start of work to rebuild their school through the government’s flagship rebuilding programme.
Great Coates Primary School in Grimsby is one of 8 schools across North and North East Lincolnshire to be rebuilt through the £4.4 billion priority school building programme ( PSBP ) , which is transforming some of the most run-down schools in the country.
As a result of £3.8 million worth of construction - due for completion by May 2016 - the school’s 1970s-era building will be replaced with a modern 2-storey facility, with bright new classrooms and a sports hall which will also be available for use by the wider community.
To mark the start of construction, an official ceremony is being held at the new site, with pupils burying a metal cylindrical time capsule containing examples of their work, class photos and details of who attended the ceremony.
Schools Minister Lord Nash said:
Our investment in school buildings across the country is transforming the learning environment for tens of thousands of pupils and their teachers.
The start of construction at Great Coates Primary School is a key milestone for the priority school building programme in North and North East Lincolnshire.
Ensuring all children have access to the best possible schools and facilities is just one part of our commitment to help all young people reach their potential regardless of their background. These buildings will provide modern, fit-for-purpose schools for pupils for many years to come.
Anna Coney, Headteacher of Great Coates Primary School, said:
Children and staff have enjoyed collecting items to bury with the capsule, and this ceremony will mark the start of an exciting new beginning for Great Coates Primary and the community. Work is already underway and all the initial plans are becoming a reality - it is the talking point for our children.
From this point, the new school will really start to take shape. It’s a tremendously exciting time for everybody connected with Great Coates Primary.
Jon Marston of Galliford Try said:
We are delighted to have started construction works on site, having spent many months working with the school and the EFA designing and planning the project. The school is being built by using modern construction techniques with large sections being manufactured off site. This will see the new school being constructed very quickly and will ensure that the children and staff will have a high-quality, modern education environment.
Thanks to the PSBP , school buildings are being rebuilt faster and cheaper than those built under the previous school building initiative - Building Schools for the Future ( BSF ). Under the BSF it took 3 years for construction work to begin. This was slashed to 1 year for the PSBP , with projects costing around a third less.
A total of 537 schools will benefit from construction through the 2 phases of the PSBP .
Central newsdesk 020 7783 8300
General enquiries 0370 000 2288
Published: 2 October 2015


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3. Building a JIT: Per-function Lazy Compilation¶
This tutorial is under active development. It is incomplete and details may change frequently. Nonetheless we invite you to try it out as it stands, and we welcome any feedback.
3.1. Chapter 3 Introduction¶
Welcome to Chapter 3 of the “Building an ORC-based JIT in LLVM” tutorial. This chapter discusses lazy JITing and shows you how to enable it by adding an ORC CompileOnDemand layer the JIT from Chapter 2.
3.2. Lazy Compilation¶
When we add a module to the KaleidoscopeJIT class from Chapter 2 it is immediately optimized, compiled and linked for us by the IRTransformLayer, IRCompileLayer and RTDyldObjectLinkingLayer respectively. This scheme, where all the work to make a Module executable is done up front, is simple to understand and its performance characteristics are easy to reason about. However, it will lead to very high startup times if the amount of code to be compiled is large, and may also do a lot of unnecessary compilation if only a few compiled functions are ever called at runtime. A truly “just-in-time” compiler should allow us to defer the compilation of any given function until the moment that function is first called, improving launch times and eliminating redundant work. In fact, the ORC APIs provide us with a layer to lazily compile LLVM IR: CompileOnDemandLayer.
The CompileOnDemandLayer class conforms to the layer interface described in Chapter 2, but its addModule method behaves quite differently from the layers we have seen so far: rather than doing any work up front, it just scans the Modules being added and arranges for each function in them to be compiled the first time it is called. To do this, the CompileOnDemandLayer creates two small utilities for each function that it scans: a stub and a compile callback. The stub is a pair of a function pointer (which will be pointed at the function’s implementation once the function has been compiled) and an indirect jump through the pointer. By fixing the address of the indirect jump for the lifetime of the program we can give the function a permanent “effective address”, one that can be safely used for indirection and function pointer comparison even if the function’s implementation is never compiled, or if it is compiled more than once (due to, for example, recompiling the function at a higher optimization level) and changes address. The second utility, the compile callback, represents a re-entry point from the program into the compiler that will trigger compilation and then execution of a function. By initializing the function’s stub to point at the function’s compile callback, we enable lazy compilation: The first attempted call to the function will follow the function pointer and trigger the compile callback instead. The compile callback will compile the function, update the function pointer for the stub, then execute the function. On all subsequent calls to the function, the function pointer will point at the already-compiled function, so there is no further overhead from the compiler. We will look at this process in more detail in the next chapter of this tutorial, but for now we’ll trust the CompileOnDemandLayer to set all the stubs and callbacks up for us. All we need to do is to add the CompileOnDemandLayer to the top of our stack and we’ll get the benefits of lazy compilation. We just need a few changes to the source:
...
#include "llvm/ExecutionEngine/SectionMemoryManager.h"
#include "llvm/ExecutionEngine/Orc/CompileOnDemandLayer.h"
#include "llvm/ExecutionEngine/Orc/CompileUtils.h"
...
...
class KaleidoscopeJIT {
private:
std::unique_ptr<TargetMachine> TM;
const DataLayout DL;
RTDyldObjectLinkingLayer ObjectLayer;
IRCompileLayer<decltype(ObjectLayer), SimpleCompiler> CompileLayer;
using OptimizeFunction =
std::function<std::shared_ptr<Module>(std::shared_ptr<Module>)>;
IRTransformLayer<decltype(CompileLayer), OptimizeFunction> OptimizeLayer;
std::unique_ptr<JITCompileCallbackManager> CompileCallbackManager;
CompileOnDemandLayer<decltype(OptimizeLayer)> CODLayer;
public:
using ModuleHandle = decltype(CODLayer)::ModuleHandleT;
First we need to include the CompileOnDemandLayer.h header, then add two new members: a std::unique_ptr<JITCompileCallbackManager> and a CompileOnDemandLayer, to our class. The CompileCallbackManager member is used by the CompileOnDemandLayer to create the compile callback needed for each function.
KaleidoscopeJIT()
: TM(EngineBuilder().selectTarget()), DL(TM->createDataLayout()),
ObjectLayer([]() { return std::make_shared<SectionMemoryManager>(); }),
CompileLayer(ObjectLayer, SimpleCompiler(*TM)),
OptimizeLayer(CompileLayer,
[this](std::shared_ptr<Module> M) {
return optimizeModule(std::move(M));
}),
CompileCallbackManager(
orc::createLocalCompileCallbackManager(TM->getTargetTriple(), 0)),
CODLayer(OptimizeLayer,
[this](Function &F) { return std::set<Function*>({&F}); },
*CompileCallbackManager,
orc::createLocalIndirectStubsManagerBuilder(
TM->getTargetTriple())) {
llvm::sys::DynamicLibrary::LoadLibraryPermanently(nullptr);
}
Next we have to update our constructor to initialize the new members. To create an appropriate compile callback manager we use the createLocalCompileCallbackManager function, which takes a TargetMachine and a JITTargetAddress to call if it receives a request to compile an unknown function. In our simple JIT this situation is unlikely to come up, so we’ll cheat and just pass ‘0’ here. In a production quality JIT you could give the address of a function that throws an exception in order to unwind the JIT’d code’s stack.
Now we can construct our CompileOnDemandLayer. Following the pattern from previous layers we start by passing a reference to the next layer down in our stack – the OptimizeLayer. Next we need to supply a ‘partitioning function’: when a not-yet-compiled function is called, the CompileOnDemandLayer will call this function to ask us what we would like to compile. At a minimum we need to compile the function being called (given by the argument to the partitioning function), but we could also request that the CompileOnDemandLayer compile other functions that are unconditionally called (or highly likely to be called) from the function being called. For KaleidoscopeJIT we’ll keep it simple and just request compilation of the function that was called. Next we pass a reference to our CompileCallbackManager. Finally, we need to supply an “indirect stubs manager builder”: a utility function that constructs IndirectStubManagers, which are in turn used to build the stubs for the functions in each module. The CompileOnDemandLayer will call the indirect stub manager builder once for each call to addModule, and use the resulting indirect stubs manager to create stubs for all functions in all modules in the set. If/when the module set is removed from the JIT the indirect stubs manager will be deleted, freeing any memory allocated to the stubs. We supply this function by using the createLocalIndirectStubsManagerBuilder utility.
// ...
if (auto Sym = CODLayer.findSymbol(Name, false))
// ...
return cantFail(CODLayer.addModule(std::move(Ms),
std::move(Resolver)));
// ...
// ...
return CODLayer.findSymbol(MangledNameStream.str(), true);
// ...
// ...
CODLayer.removeModule(H);
// ...
Finally, we need to replace the references to OptimizeLayer in our addModule, findSymbol, and removeModule methods. With that, we’re up and running.
To be done:
** Chapter conclusion.**
3.3. Full Code Listing¶
Here is the complete code listing for our running example with a CompileOnDemand layer added to enable lazy function-at-a-time compilation. To build this example, use:
# Compile
clang++ -g toy.cpp `llvm-config --cxxflags --ldflags --system-libs --libs core orcjit native` -O3 -o toy
# Run
./toy
Here is the code:
//===- KaleidoscopeJIT.h - A simple JIT for Kaleidoscope --------*- C++ -*-===//
//
// The LLVM Compiler Infrastructure
//
// This file is distributed under the University of Illinois Open Source
// License. See LICENSE.TXT for details.
//
//===----------------------------------------------------------------------===//
//
// Contains a simple JIT definition for use in the kaleidoscope tutorials.
//
//===----------------------------------------------------------------------===//
#ifndef LLVM_EXECUTIONENGINE_ORC_KALEIDOSCOPEJIT_H
#define LLVM_EXECUTIONENGINE_ORC_KALEIDOSCOPEJIT_H
#include "llvm/ADT/STLExtras.h"
#include "llvm/ExecutionEngine/ExecutionEngine.h"
#include "llvm/ExecutionEngine/JITSymbol.h"
#include "llvm/ExecutionEngine/RTDyldMemoryManager.h"
#include "llvm/ExecutionEngine/RuntimeDyld.h"
#include "llvm/ExecutionEngine/SectionMemoryManager.h"
#include "llvm/ExecutionEngine/Orc/CompileOnDemandLayer.h"
#include "llvm/ExecutionEngine/Orc/CompileUtils.h"
#include "llvm/ExecutionEngine/Orc/IRCompileLayer.h"
#include "llvm/ExecutionEngine/Orc/IRTransformLayer.h"
#include "llvm/ExecutionEngine/Orc/LambdaResolver.h"
#include "llvm/ExecutionEngine/Orc/RTDyldObjectLinkingLayer.h"
#include "llvm/IR/DataLayout.h"
#include "llvm/IR/LegacyPassManager.h"
#include "llvm/IR/Mangler.h"
#include "llvm/Support/DynamicLibrary.h"
#include "llvm/Support/raw_ostream.h"
#include "llvm/Target/TargetMachine.h"
#include "llvm/Transforms/Scalar.h"
#include "llvm/Transforms/Scalar/GVN.h"
#include <algorithm>
#include <memory>
#include <set>
#include <string>
#include <vector>
namespace llvm {
namespace orc {
class KaleidoscopeJIT {
private:
std::unique_ptr<TargetMachine> TM;
const DataLayout DL;
RTDyldObjectLinkingLayer ObjectLayer;
IRCompileLayer<decltype(ObjectLayer), SimpleCompiler> CompileLayer;
using OptimizeFunction =
std::function<std::shared_ptr<Module>(std::shared_ptr<Module>)>;
IRTransformLayer<decltype(CompileLayer), OptimizeFunction> OptimizeLayer;
std::unique_ptr<JITCompileCallbackManager> CompileCallbackManager;
CompileOnDemandLayer<decltype(OptimizeLayer)> CODLayer;
public:
using ModuleHandle = decltype(CODLayer)::ModuleHandleT;
KaleidoscopeJIT()
: TM(EngineBuilder().selectTarget()), DL(TM->createDataLayout()),
ObjectLayer([]() { return std::make_shared<SectionMemoryManager>(); }),
CompileLayer(ObjectLayer, SimpleCompiler(*TM)),
OptimizeLayer(CompileLayer,
[this](std::shared_ptr<Module> M) {
return optimizeModule(std::move(M));
}),
CompileCallbackManager(
orc::createLocalCompileCallbackManager(TM->getTargetTriple(), 0)),
CODLayer(OptimizeLayer,
[](Function &F) { return std::set<Function*>({&F}); },
*CompileCallbackManager,
orc::createLocalIndirectStubsManagerBuilder(
TM->getTargetTriple())) {
llvm::sys::DynamicLibrary::LoadLibraryPermanently(nullptr);
}
TargetMachine &getTargetMachine() { return *TM; }
ModuleHandle addModule(std::unique_ptr<Module> M) {
// Build our symbol resolver:
// Lambda 1: Look back into the JIT itself to find symbols that are part of
// the same "logical dylib".
// Lambda 2: Search for external symbols in the host process.
auto Resolver = createLambdaResolver(
[&](const std::string &Name) {
if (auto Sym = CODLayer.findSymbol(Name, false))
return Sym;
return JITSymbol(nullptr);
},
[](const std::string &Name) {
if (auto SymAddr =
RTDyldMemoryManager::getSymbolAddressInProcess(Name))
return JITSymbol(SymAddr, JITSymbolFlags::Exported);
return JITSymbol(nullptr);
});
// Add the set to the JIT with the resolver we created above and a newly
// created SectionMemoryManager.
return cantFail(CODLayer.addModule(std::move(M), std::move(Resolver)));
}
JITSymbol findSymbol(const std::string Name) {
std::string MangledName;
raw_string_ostream MangledNameStream(MangledName);
Mangler::getNameWithPrefix(MangledNameStream, Name, DL);
return CODLayer.findSymbol(MangledNameStream.str(), true);
}
void removeModule(ModuleHandle H) {
cantFail(CODLayer.removeModule(H));
}
private:
std::shared_ptr<Module> optimizeModule(std::shared_ptr<Module> M) {
// Create a function pass manager.
auto FPM = llvm::make_unique<legacy::FunctionPassManager>(M.get());
// Add some optimizations.
FPM->add(createInstructionCombiningPass());
FPM->add(createReassociatePass());
FPM->add(createGVNPass());
FPM->add(createCFGSimplificationPass());
FPM->doInitialization();
// Run the optimizations over all functions in the module being added to
// the JIT.
for (auto &F : *M)
FPM->run(F);
return M;
}
};
} // end namespace orc
} // end namespace llvm
#endif // LLVM_EXECUTIONENGINE_ORC_KALEIDOSCOPEJIT_H
Next: Extreme Laziness – Using Compile Callbacks to JIT directly from ASTs


These documents describe in detail the data we have used to calculate the 2014 to 2015 education services grant (
ESG
) rates. We provide details on the transfer from local government revenue funding in 2014 to 2015 and the relevant pupil numbers.
We include calculations of the
ESG
rates and the
ESG
allocations to local authorities.


Open Until Filled
GENERAL DESCRIPTION:
The Wyoming Department of Transportation (WYDOT) is an agency committed to providing a safe, high quality, and efficient transportation system for the State of Wyoming. We are currently seeking a Records and Data Management Specialist I position for the Highway Safety Program located in Cheyenne, Wyoming. The purpose of this position is to supply specified crash data to a number of WYDOT Engineers and agencies, law enforcement, Federal DOT, and other private individuals, including private organizations, media, and educational institutions, all requiring an extensive knowledge of multiple and relational database systems, to increase the safety of our state transportation system.
Cheyenne is a steadily growing community along the Front Range but still true to the history of the Old West. The city offers nearby access to mountain biking, skiing, hiking, fishing, hunting, and other outdoor activities. Cheyenne also is home to the "Daddy of 'em All" – Cheyenne Frontier Days – held every last week of July. Wyoming is one of only seven states with no state income tax.
Human Resource Contact:<PHONE_NUMBER>
ESSENTIAL FUNCTIONS: The listed functions are illustrative only and are not intended to describe every function which may be performed in the job level.
- Creates comprehensive traffic studies for use by WYDOT district engineers, traffic engineers, planning engineers, engineering consulting firms, attorneys, law enforcement agencies at the federal, state, county, and city levels, media, private individuals, other government agencies and educational institutions.
- Constructs complex database queries with database linkage and statistical analysis based on specific requests from contacts to disseminate accurate data to our safety partners.
- Conducts high level analysis on core safety components (alcohol, drugs, speed, distracted driving, etc.) and their effect on critical and serious crashes; identifying statistically significant data trends using percentages, averages, and trendlines for crash data statewide or a specific subset of data.
- Complies with the FARS (Fatality Analysis Reporting System) agreement with the National Highway Traffic Safety Administration (NHTSA) to provide and code fatal crash information according to specific guidelines set forth by NHTSA and NISR (National Institute for Safety Research) for the purpose of national research on fatal traffic crashes.
- Attends all required training, conferences, and committee meetings.
- Communicates between law enforcement, the Department of Health Vital Statistics Office, the State Laboratory, the Department of Criminal Investigation, and the County Coroners Offices for chemical testing information regarding drugs and alcohol.
- Responds to requests for Wyoming licensed driver and Wyoming registered vehicle information from FARS Analysts in the other 49 states through the FARS CDAN application.
- Maintains strict confidentiality due to access of personal, medical, and sensitive information.
- Provides training on the proper procedures for entering urban location information for traffic crashes in paper and electronic formats.
- Utilizes a variety of resources and software to accurately locate crash sites and trains others on pinpointing the location of crashes through data provided on drop-down menus.
- Provides work direction to lower level positions.
PREFERENCES:
Preference may be given to individuals who have knowledge of national coding standards for traffic crashes, as well as specialized Highway Safety software.
KNOWLEDGE:
- Knowledge of theories, principles and practices of archival science
- Knowledge of GIS, GPS, and various mapping resources and software
- Knowledge of Microsoft Office, including Excel and Word
- Knowledge of relational database systems, database management, and syntax style queries
- Knowledge of statistical analysis and research
- Ability to effectively communicate with multiple agencies and media sources.
- Ability to employ effective listening techniques, problem solving skills, structured logic, multi-task, analyze large amounts of data, and write complex database queries.
MINIMUM QUALIFICATIONS:
Education:
Bachelor's Degree (typically in Records or Data Management)
Experience:
0-1 year of progressive work experience (typically in Records and Data Management) with acquired knowledge at the level of a Records & Data Management Clerk
OR
Education & Experience Substitution:
3-4 years of progressive work experience (typically in Records and Data Management) with acquired knowledge at the level of a Records & Data Management Clerk
Certificates, Licenses, Registrations:
None
045-Department of Transportation - WYDOT-Operations - Highway Safety
Click here to view the State of Wyoming Classification and Pay Structure.
URL: http://agency.governmentjobs.com/wyoming/default.cfm
The State of Wyoming is an Equal Opportunity Employer and actively supports the ADA and reasonably accommodates qualified applicants with disabilities.
Class Specifications are subject to change, please refer to the A & I HRD Website to ensure that you have the most recent version.


If you’re a newcomer, check out the Good first issue and Help wanted labels in the Contour repository.
Join the Contour Office Hours, a place where you can ask questions like “how do I do this in Contour” and “why does Contour do this thing this way?”
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Browse through our list of Home Decor Items
Browse through our list of Home Decor Items
Flash sale on living room and bedroom furniture
Bring the best out of the master chef in you!
Red hot deals at affordable prices. Check out our clearance section for more details.


The OINK "version" is the date when it was released, such as 1 Feb 2011. OINK and MR-MPI library are updated continuously. Whenever we fix a bug or add a feature, we release it immediately, and post a notice on this page of the WWW site. Each dated copy of OINK contains all the features and bug-fixes up to and including that version date. The version date is printed to the screen and log file every time you run OINK. It is also in the file oink/version.h and in the MR-MPI directory name created when you unpack a tarball.
OINK is a simple scripting wrapper around the "MapReduce-MPI library, and also provides a easy-to-use development framework for writing new MapReduce algorithms and codes. Like the MR-MPI library, OINK will run on any platform (serial or parallel) that supports MPI. Note the MR-MPI library has its own manual and doc pages.
The name OINK is meant to evoke the aroma of the Apache Pig platform which wraps the Hadoop MapReduce capabilities with its high-level Pig Latin language. Since OINK has only a small fraction of Pig's capability, it is more the sound of a pig, than the pig itself.
Source code for OINK and the MR-MPI library were developed at Sandia National Laboratories, a US Department of Energy facility. They are freely available for download from the MR-MPI web site and are distributed under the terms of the modified Berkeley Software Distribution (BSD) License. This basically means they can be used by anyone for any purpose. See the LICENSE file provided with the distribution for more details.
The authors of OINK and the MR-MPI library are Steve Plimpton at and Karen Devine who can be contacted via email: sjplimp,kddevin at sandia.gov.
We think the first two goals are largely met. See the section on Adding Commands to OINK and the named command, input, and output doc pages for details of the first goal. See the section on Adding Functions to OINK for details of the second goal.
The third goal, however, is only partially met. See the MR-MPI library commands doc page for its current status. The sticking point here is that in a real programming language you can pass a pointer to an arbitrary data structure to your map() or reduce() functions, but it is hard to do that from a scripting language using text input without re-inventing something like Python.
OINK aims to be a simple scripting interface and development environment and the lightweight documentation reflects that.
Once you are familiar with OINK, you may want to bookmark this page at Section_script.html#comm since it gives quick access to documentation for all OINK commands.
PDF file of the entire manual, generated by htmldoc


Steamed Fresh Fish
Materials
Fresh fish,Ginger, Spring Onion, Soy Sauce
Process
Cleaning out the fish viscera out and slice 2 strokes on fish back
Put the steam rack in and boiled the water
Put the fish on the rack and steam
Steam for a while according to the weight (if the fish weight around 1.1 lb,steam for 6 minutes)
Stir fry the shredded ginger and sliced spring onion
Take the fish out and pour the hot oil with ginger and spring onion
Pour soy sauce to add more tastes
Story
I used to enjoy this dish very much in my childhood and as growing up I lost my interest in it. It is common to eat in my hometown. In addition, it is my father's favorite dish so my mother cooks it when my father return home for meal. It attaches to plenty of things in my family. Even we have the same dish in various restaurants, but I think my mother's version is the best of all and I miss it very much after leaving home for such a long time.


Resting-state Functional MRI (rsfMRI)¶
Synaptic dysfunction has long been hypothesized to be an early event in AD degeneration, and is likely to be reflected in fMRI connectivity. To derive a functional connectivity map, one needs to specify an anatomical location, or use some data driven technique such as a bootstrap analysis of stable clusters (BASC) (Bellec et al. 2010) to generate a group template of resting-state networks, here the DMN (panel a). Average time series within the target region/network are derived from a series of individual datasets (panel b), and correlated with the time series of all voxels across the brain, resulting into individual fc-maps (panel c). Promising results were first reported in the literature on cross-sectional comparisons of fc-maps between patients with AD dementia and cognitively normal (CN) elderly subjects (e.g. REFS), as well a comparisons of patients with MCI of the amnestic type and CN (e.g. ). Although most published studies feature low sample size, two recent meta-analysis from my group, one combining imaging data of N=255 in CN and MCI participants across four studies (Tam et al. 2015), and another one combining published coordinates from 34 published studies, including N=1363 individuals, point to a consistent dysconnectivity in regions of the default-mode network, as well as alterations in limbic and fronto-parietal networks. In addition to these clinical comparisons, several studies have reported differences in resting-state connectivity between amyloid beta positive vs negative CN elderly subjects, e.g. (Sheline et al. 2010), as well as differences between CN participants with and without a family history of AD. Overall, despite still being in its infancy, there is solid evidence at this stage in the literature that rs-fMRI is an early, sensitive marker of the progression of AD (Vemuri, Jones, and Jack 2012).
fMRIprep Pipeline¶
The fMRIprep pipeline, developed by the Poldrack lab at Stanford University, performs basic processing steps (coregistration, normalization, unwarping, noise component extraction, segmentation, skullstripping etc.) providing outputs that can be easily submitted to a variety of group level analyses, including task-based or resting-state fMRI, graph theory measures, surface or volume-based statistics, etc. The fMRIPrep pipeline uses a combination of tools from well-known software packages, including FSL, ANTs, FreeSurfer and AFNI. This pipeline was designed to provide the best software implementation for each state of preprocessing.
The CCNA dataset is processed using fMRIprep version 20.2.1 LTS, which is based on Nipype 1.5.1. Many internal operations of fMRIPrep use Nilearn 0.6.2, mostly within the functional processing workflow. For more details of the pipeline, see [the section corresponding to workflows in fMRIPrep's documentation](https://fmriprep.readthedocs.io/en/latest/workflows.html "FMRIPrep's documentation"). Processing scripts will be made available on github. A full description The log files for execution will be included with the derivatives and can be accessed through the PSOM interface.
Structural processing¶
The T1-weighted (T1w) images were corrected for intensity non-uniformity (INU) with `N4BiasFieldCorrection`, distributed with ANTs 2.3.3, and used as T1w-reference throughout the workflow. The T1w-reference was then skull-stripped with a Nipype implementation of the `antsBrainExtraction.sh` workflow (from ANTs), using OASIS30ANTs as target template. Brain tissue segmentation of cerebrospinal fluid (CSF), white-matter (WM) and gray-matter (GM) were performed on the brain-extracted T1w using `fast` (FSL 5.0.9). Brain surfaces were reconstructed using `recon-all` (FreeSurfer 6.0.1), and the brain mask estimated previously was refined with a custom variation of the method to reconcile ANTs-derived and FreeSurfer-derived segmentations of the cortical gray-matter of Mindboggle. Volume-based spatial normalization to two standard spaces (MNI152NLin2009cAsym, MNI152NLin6Asym) was performed through nonlinear registration with `antsRegistration` (ANTs 2.3.3), using brain-extracted versions of both T1w reference and the T1w template. The following templates were selected for spatial normalization: ICBM 152 Nonlinear Asymmetrical template version 2009c, and FSL's MNI ICBM 152 non-linear 6th Generation Asymmetric Average Brain Stereotaxic Registration Model.
Note
For more information on the Freesurfer steps and processing please see the section on sMRI.
Functional processing¶
Preprocessing¶
For each of the 1 BOLD runs found per subject (across all tasks and sessions), the following preprocessing was performed. First, a reference volume and its skull-stripped version were generated using a custom methodology of fMRIPrep. Susceptibility distortion correction (SDC) was omitted. The BOLD reference was then co-registered to the T1w reference using `bbregister` (FreeSurfer) which implements boundary-based registration. Co-registration was configured with six degrees of freedom. Head-motion parameters with respect to the BOLD reference (transformation matrices, and six corresponding rotation and translation parameters) are estimated before any spatiotemporal filtering using `mcflirt` (FSL 5.0.9). BOLD runs were slice-time corrected using `3dTshift` from AFNI 20160207. The BOLD time-series (including slice-timing correction when applied) were resampled onto their original, native space by applying the transforms to correct for head-motion. These resampled BOLD time-series will be referred to as preprocessed BOLD in original space, or just preprocessed BOLD. The BOLD time-series were resampled into standard space, generating a preprocessed BOLD run in MNI152NLin2009cAsym space. First, a reference volume and its skull-stripped version were generated using a custom methodology of fMRIPrep. Automatic removal of motion artifacts using independent component analysis (ICA-AROMA) was performed on the preprocessed BOLD on MNI space time-series after removal of non-steady state volumes and spatial smoothing with an isotropic, Gaussian kernel of 6mm FWHM (full-width half-maximum). Corresponding "non-aggresively" denoised runs were produced after such smoothing. Additionally, the "aggressive" noise-regressors were collected and placed in the corresponding confounds file. Several confounding time-series were calculated based on the preprocessed BOLD: framewise displacement (FD), DVARS and three region-wise global signals. FD was computed using two formulations following Power (absolute sum of relative motions, power_fd_dvars) and Jenkinson (relative root mean square displacement between affines, mcflirt). FD and DVARS are calculated for each functional run, both using their implementations in *Nipype* (following the definitions by 9power_fd_dvars). The three global signals are extracted within the CSF, the WM, and the whole-brain masks. Additionally, a set of physiological regressors were extracted to allow for component-based noise correction (CompCor). Principal components are estimated after high-pass filtering the preprocessed BOLD time-series (using a discrete cosine filter with 128s cut-off) for the two CompCor variants: temporal (tCompCor) and anatomical (aCompCor). tCompCor components are then calculated from the top 2% variable voxels within the brain mask. For aCompCor, three probabilistic masks (CSF, WM and combined CSF+WM) are generated in anatomical space. The implementation differs from that of Behzadi et al. in that instead of eroding the masks by 2 pixels on BOLD space, the aCompCor masks are subtracted a mask of pixels that likely contain a volume fraction of GM. This mask is obtained by dilating a GM mask extracted from the FreeSurfer's aseg segmentation, and it ensures components are not extracted from voxels containing a minimal fraction of GM. Finally, these masks are resampled into BOLD space and binarized by thresholding at 0.99 (as in the original implementation). Components are also calculated separately within the WM and CSF masks. For each CompCor decomposition, the k components with the largest singular values are retained, such that the retained components' time series are sufficient to explain 50 percent of variance across the nuisance mask (CSF, WM, combined, or temporal). The remaining components are dropped from consideration. The head-motion estimates calculated in the correction step were also placed within the corresponding confounds file. The confound time series derived from head motion estimates and global signals were expanded with the inclusion of temporal derivatives and quadratic terms for each (confounds_satterthwaite_2013). Frames that exceeded a threshold of 0.5 mm FD or 1.5 standardised DVARS were annotated as motion outliers. All resamplings can be performed with a single interpolation step by composing all the pertinent transformations (i.e. head-motion transform matrices, susceptibility distortion correction when available, and co-registrations to anatomical and output spaces). Gridded (volumetric) resamplings were performed using `antsApplyTransforms` (ANTs), configured with Lanczos interpolation to minimize the smoothing effects of other kernels. Non-gridded (surface) resamplings were performed using `mri_vol2surf` (FreeSurfer).
Quality control¶
Outputs of the fMRIprep pipeline will be subjected to a careful visual inspection and the results quality calls, along with head motion statistics, will be made available on the fMRIprep description. Estimates of the maximum motion (translation and rotation) between consecutive functional volumes for each rs-fMRI dataset will be inspected to categorize the datasets as containing minimal (<1mm or degree), moderate (2 to 3 mm or degrees) or severe motion (>3 mm or degrees). The individual results of the fMRIprep pipeline will be visually inspected for quality of the registration between rs-fMRI and s-MRI data, registration of s-MRI data to template space, and for common artefacts such as ghosting and signal loss. In the case of identification of substandard registration outcomes, a parameter controlling the non-uniformity correction of the s-MRI will be adjusted and the analysis repeated until the coregistration results is satisfactory.
Quality control outputs will include:
motion statistics distributed in comma-seperated values format (.csv) for each site
average structural scans after linear and non-linear transformations in compressed nifti format (.nii.gz).
average functional scans after linear and non-linear transformations in compressed nifti format
average of all anatomical brain masks for each site of the training and test samples in compressed nifti format (.nii.gz)
average of all functional brain masks for each site of the training and test samples are included as compressed nifti format (.nii.gz)
Note
Packages for quality control: registration in particular
1http://www.nitrc.org/plugins/mwiki/index.php/neurobureau:fMRIprepPipeline 2http://en.wikibooks.org/wiki/MINC 3http://www.nitrc.org/rs/?group_id=411 4https://github.com/SIMEXPfmriprep 5http://psom.simexp-lab.org/how_to_use_psom.html


---
layout: post
title: Regarding secret, hidden sin...
date: '2009-05-23T15:23:00.003-05:00'
author: Jabell
tags:
- Quotes
- Christian Living
- Sin
modified_time: '2009-05-23T15:26:38.551-05:00'
blogger_id: tag:blogger.com,1999:blog-19739956.post-6676822525674047684
blogger_orig_url: http://theabellsix.blogspot.com/2009/05/regarding-secret-hidden-sin.html
---
Douglas Wilson writes,
Three solutions present themselves—two of them false and one true. The first false solution is to continue to hide the sin, on one's own terms, and in one's own way. But Moses' words should follow all who seek this way out—"be sure your sin will find you out." The second seeks to combine biblical truths with pragmatic solutions. "I confessed it to God. What else . . .?" Sometimes there is nothing else but to receive forgiveness. But in other situations, much remains to be done. Stolen goods must still be restored, slandered brothers and sisters must be asked for forgiveness, and broken covenants must be put right. And so the third way, the only effective way, is to want God's mercy so much that you are willing do exactly what He says when you apply to Him for it.Read the whole thing.